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Physical Layer Impairments in the Optimization of the Next-Generation of All-Optical Networks 3 Vishwanath & Liang (2005) examine the problem of online multicast routing in mesh transport networks without the capability for conversion of wavelengths, by dividing wavelengths in multiple time slots and multiplexing the traffic. The goal is to route the multicast traffic efficiently by using grooming while balancing the connection loads. Likewise in Sahasrabuddhe & Mukherjee (1999), they point out that multicast applications can be efficiently routed using light-tree (this improves throughput and network performance). Sreenath et al. (2006) address the problem of routing and the assigning of wavelengths in multicast sessions with low capacity demands in WDM networks with sparse splitting capacity. For this reason only a few nodes on the network are able to split traffic. Nevertheless those nodes not able to split can do so with OEO conversions. They point out that the splitting of traffic is more expensive at the electronic level than at the optic level because of the delays caused by OEO conversion. Liao et al. (2006) explore the dynamic problem of WDM mesh networks with MTG to analyze and improve the blocking probability, by proposing an algorithm based on light-tree integrated with grooming. The results after using it show its usefulness. The blocking probability is reduced while taking advantage of the resources of the network under low restrictions of non conversion of wavelength and a limited number of wavelengths and transceivers. They divide the problem into three sub-sections: i ) defining the virtual topology using light tree, ii ) routing the connection applications across the physical topology and optimally assigning the wavelengths for the multicast tree and, iii ) grooming low speed traffic in the virtual topology. Khalil et al. (2006) explore the problem of providing dynamic low speed connections unicast and multicast in mesh WDM networks. They focus on the dynamic construction of the logic topology, where the lightpath and the light-tree are configured according to the traffic demands. They also propose using all resources efficiently in order to decrease the blocking probability. This is how they propose several heuristic sequential techniques, by breaking down the problem into four parts: 1. Routing problem 2. Logic topology design 3. Problem of providing wavelengths 4. TG problem Huang et al. (2005) also analyze the blocking probability. Nevertheless, they also analyze when there are sparse splitting capacities. The algorithm that they proposed is based on light-tree dynamics that support multihop. The algorithm can be dropped and branched and can establish a new path when an application is received or alter itself when there are existing path free of traffic. The components mentioned carry out the process of grooming by using OEO conversions when multicast and unicast traffics are jointly multiplexed. 1.2 Routing unicast and multicast traffic together In WDM networks, there are two typical all-optical communication channels, lightpaths and light-trees (Kamat (2006)). A lightpath is an all-optical communication channel that passes through all intermediate nodes between a source and a single destination without 315 Physical Layer Impairments in the Optimization of the Next-Generation of All-Optical Networks 4 Will-be-set-by-IN-TECH OEO conversion. A light-tree is an all-optical channel between a single source and multiple destinations. Like the lightpath, there is no OEO conversion at any intermediate node on a light-tree. Using a light-tree to carry multicast traffic is a natural choice in WDM mesh networks. Many researches have addressed the very fundamental multicast routing and wavelength-assignment problem, such as in (Liao et al., 2006; Singhal et al., 2006; Sreenath et al., 2006; Ul-Mustafa & Kamal, 2006). In these studies, proposals for handling static and dynamic traffic has been made. Proposals have focused on mathematical models based on ILP (Integer Linear Programming) and heuristic techniques based on minimum-cost steiner tree. All these studies used a node architecture similar to that employed in Singhal et al. (2006), which employs Optical Splitters for the duplication of traffic. However, these proposals do not take into account the optimal routing of unicast and multicast traffic together. Huang et al. (2005) tackled the problem of routing traffic unicast/multicast together. They address the online multicast traffic grooming problem in wavelength-routed WDM mesh networks with sparse grooming capability. The architecture node that employ them provide: optical multicasting and electronic grooming. The basic component of the architecture is a SaD Switch, which has configurable Splitters. The routing, allocation and grooming problem has been initially resolved with off-line techniques. Sahasrabuddhe & Mukherjee (1999) presents a mathematical model (MILP) with opaque nodes (OEO conversions) and wavelength continuity constraint for the type broadcast traffic. Billah et al., 2003; Zsigri et al., 2003 employs heuristics that use Shortest path and First Fit for the routing and allocation of wavelengths. Additionally, it must be taken into account that not all nodes have multicast capabilities (sparse splitting). Recently the work has been focused on the analysis of dynamic traffic. Vishwanath & Liang (2005) proposes an Adaptive Shortest Path Tree (ASPT) using Dijkstra’s algorithm that takes into account a function of cost to minimize implementation costs. Khalil et al. (2006) divides the problem into: i ) routing, ii) logical topology, iii) provisioning and iv) traffic grooming. This makes it possible to minimize the blocking probabilities in transparent networks. In previous works, different algorithms have been used to handle the traffic unicast and multicast together but taking into account electronical grooming and OEO conversions. Below, we describe the problems of using the architectures mentioned. 1.2.1 Problem definitions In this section, an example is used to explain the disadvantages of the classical methods used for routing unicast and multicast traffic. Let us consider a subset of the NSFNet network of 14 nodes interconnected through optical links (Figure 1). Three sessions are considered: i ) S 1 being a unicast session {N 3 }→{N 6 }, where the node N 3 is the source node and the node N 6 is the destination; ii) S 2 being a multicast session {N 3 }→{N 6 , N 7 }, where N 6 and N 7 are the destinations nodes, and iii ) S 3 being a unicast session {N 5 }→{N 7 }, where the node N 5 is the source node and the node N 7 is the destination. Routing these two sessions can be performed in the following ways: Light-trees (Singhal et al. (2006), Figure 2): sessions S 1 and S 2 are both routed through the same wavelength. In this case, no OEO conversions are used but traffic cannot be differentiated. As a consequence, all groomed traffic in a light-tree is routed to all 316 Optical Fiber Communications and Devices Physical Layer Impairments in the Optimization of the Next-Generation of All-Optical Networks 5 Fig. 1. NSFNet network. Sessions S 1 and S 2 in nodes N 3 , N 5 , N 6 and N 7 destinations. In this example, since the S 1 traffic should not be sunk at node N 7 , there is bandwidth wastage. When a new request arrives (S 3 ) a new lightpath (N 5 → N 7 )isset up. Fig. 2. Example Light-tree, Unicast S 1 : {N 3 }→{N 6 }, Multicast S 2 : {N 3 }→{N 6 , N 7 }, and Unicast S 3 : {N 5 }→{N 7 } Lightpaths (Solano et al. (2007); Zhu & Mukherjee (2002), Figure 3): two lightpaths are needed for routing both sessions S 1 and S 2 . The first lightpath follows the path N 3 → N 5 → N 6 routing the sessions S 1 and S 2 . The second lightpath routes session S 2 using the path N 6 → N 5 → N 7 . It requires an additional wavelength, even though both demands could fit within one wavelength. In this case, there is also a waste of bandwidth, since spare bandwidth cannot be used. As in Light-tree, this scheme requires an additional lightpath to route S 3 . Fig. 3. Example Lightpath, Unicast S 1 : {N 3 }→{N 6 }, Multicast S 2 : {N 3 }→{N 6 , N 7 }, and Unicast S 3 : {N 5 }→{N 7 } 317 Physical Layer Impairments in the Optimization of the Next-Generation of All-Optical Networks 6 Will-be-set-by-IN-TECH Light-trails (Wu & Yeung (2006), Figure 4): one light-trail is required for routing sessions (S 1 , S 2 , S 3 ). A light-trail is an unidirectional optical bus. In the example, we can setup one between nodes N 3 and N 7 as N 3 → N 5 → N 6 → N 5 → N 7 . The disadvantage of light-trails is that the path may contain repeated nodes and the length of a light-trail is limited. Note that in our example, a wavelength is used in N 5 → N 6 and another one in N 6 → N 5 . Fig. 4. Example Light-trail, Unicast S 1 : {N 3 }→{N 6 }, Multicast S 2 : {N 3 }→{N 6 , N 7 }, and Unicast S 3 : {N 5 }→{N 7 } Link-by-Link (Huang et al. (2005), Figure 5): this scheme routes traffic allowing OEO conversions on all nodes. Three lightpaths are used: N 3 → N 5 , N 5 → N 6 and N 5 → N 7 .A lightpath routes sessions S 1 and S 2 together from node N 3 to node N 5 . Node N 5 processes electronically the traffic and forwards sessions S 1 and S 2 together through the lightpath N 5 → N 6 and, S 2 and S 3 through the lightpaths N 5 → N 7 . The wavelength bandwidth is efficiently used, however it requires more electronic processing and OEO conversions. Fig. 5. Example Link-by-Link routing, Unicast S 1 : {N 3 }→{N 6 }, Multicast S 2 : {N 3 }→{N 6 , N 7 }, and Unicast S 3 : {N 5 }→{N 7 } In particular, the problem arises when there are two (or more) sessions such as in: a) both are originated in the same root node, b ) the wavelength capacity is enough for both sessions but, c ) destination nodes of one session is a subset of the other. As we could see by our example, there is no optical architecture that can efficiently route such traffic: either residual bandwidth is wasted, or more OEO conversions are needed. While bandwidth plays an important role in the revenues of any service provider, the cost incurred by OEO conversion is the dominant cost in setting up the OTN. In general, the tendency is to setup a light-tree spanning to all possible destinations of a set of sessions, as shown in Figures 2-5. Several studies tackle this problem. Huang et al. (2005) proposes an on-line technique called MulTicast Dynamic light-tree Grooming Algorithm (MTDGA). MTDGA is an algorithm that performs multicast traffic grooming with the objective of reducing the blocking probability by multiplexing unicast and multicast together. Khalil et al. (2006) also sets out to reduce the blocking probability, however it uses separate schemes for routing and grooming multicast and unicast traffic. 318 Optical Fiber Communications and Devices Physical Layer Impairments in the Optimization of the Next-Generation of All-Optical Networks 7 1.3 Stop-and-Go Light-tree (S/G Light-tree) architecture We use Stop-and-Go Light-tree (S/G Light-tree) (Sierra et al., 2008). S/G Light-tree allows grooming unicast and multicast traffic together in a light-tree, hence reducing bandwidth wastage. An S/G Light-tree allows a node to optically drop part of the multiplexed traffic in a wavelength without incurring on OEO conversions. Hence, once the traffic is replicated, it prevents or stops the replicas from reaching undesirable destinations. Moreover, it enables a node to aggregate traffic in a passing wavelength without incurring on OEO conversions. More detailed information can be found in Sierra et al. (2008). Figure 6 shows the solution to the previous problem using an S/G Light-tree. Session S 1 is dropped at node N 5 without the need of OEO conversions of the routed traffic in the wavelength. Session S 3 is added on the same wavelength of the S/G Light-tree at node N 5 . While Link-by-link (Figure 5) and S/G Light-tree (Figure 6) efficiently use the bandwidth, the first needs OEO conversions. Fig. 6. S/G Light-tree scheme The Stop-and-Go functionality is supported by optical labels or “Traffic Tags" (TT). Each packet in a wavelength contains a header carrying a TT field. Both unicast and multicast traffic can be marked with a TT. A TT can be inserted orthogonally to the packet data. The label information is FSK modulated on the carrier phase, and the data is modulated on the carrier amplitude. Figure 7 shows this procedure. The architecture has been designed for easy detection and processing of the TT. We assume that the bit pattern interpreter in the architecture has low configuration times. Moreover, the bit pattern has to be configured for the traffic of each multicast tree. Fig. 7. S/G Light-tree Labels Figure 8 shows the used node architecture. Initially, the optical fiber traffic flows are demultiplexed in the wavelength channel (Demux). λ 2 carries the request S 1 and S 2 multiplexed electronically. S 1 is marked with a TT indicating that it should be stopped from going to N 5 . λ 2 is switched (OSW1) in the Splitter and Amplifier Bank. The splitter replicates the incoming traffic to all the node’s neighbors, regardless of the TT field. Then, for each packet replica, the TT field is extracted in order to decide whether the packet should be stopped from being forwarded to an undesired destination. 319 Physical Layer Impairments in the Optimization of the Next-Generation of All-Optical Networks 8 Will-be-set-by-IN-TECH Fig. 8. Stop-and-Go Light-tree (S/G Light-tree), node N 5 A detection system consists of FSK Demod, 1x2 Fast Switch, Bit pattern Interpreter, Contention Resolution, Idle detection and fiber delay lines (A similar detection system was proposed in Van Breusegern et al. (2006); Vlachos et al. (2003)). A small amount of power is tapped from the wavelength and redirected to the FSK Demod, where the label gets demodulated and ready for interpretation. FSK Demod sends the TT field to the Bit pattern Interpreter. The TT-field is analyzed by an all-optical correlator in the Bit pattern Interpreter block. If the interpreter-block identifies that the TT field has stopped, it communicates to its corresponding 1x2 Fast Switch in order to either drop or switch the packet towards the receiver (Rx). A multiplexer is used to reduce the number of receivers. These packets are later analyzed to decide whether they must be dropped (FREE), groomed in another S/G Light-tree or, dropped to the local network. A S/G Light-tree node allows to add traffic to the wavelength as well, only when free capacity is detected (Idle Detection). In our example, session S 3 can employ wavelength 2 with tunable lasers. S/G Light-tree also allows to add sessions using the traditional way. 2. Physical phenomena in optical fibers and the importance in WDM networks Grooming algorithms, routing and wavelength assignment (GRWA) work with the assumption that all wavelengths in the optical media have the same characteristics of transmission of bits - no bit error (Azodolmolky et al., 2011). However, the optical fiber presents some phenomena that impair the transmission quality of the light-trees. Physical phenomena that may occur in the fiber is divided into two: 1. Linear optical effects: spontaneous amplification, spontaneous emission (ASE), polarization mode dispersion (PMD), chromatic dispersion. 2. Non-linear optical effects: Four-wave mixing (FWM), Selfphase modulation (SPM), Cross-phase modulation (XPM), Stimulated Raman scattering (SRS). 320 Optical Fiber Communications and Devices Physical Layer Impairments in the Optimization of the Next-Generation of All-Optical Networks 9 Current work studying PMD, ASE, FWM algorithms applied to routing and wavelength assignment (without grooming), taking into account the effect of power, frequency, wavelength and length of the connection (Ali Ezzahdi et al., 2006). In this chapter, we propose a predictive model of allocation of wavelengths based on Markov chains. The model takes into account the residual dispersion in WDM networks with traffic grooming and support the applications unicast/multicast with QoS requirements. 2.1 Allocation model wavelengths, taking into account chromatic dispersion Some definitions and/or parameters used: • We define 3 classes of service (CoS) for different traffic or sessions that will use the transport network. The CoS are: High Priority (CoS A ), Medium Priority (CoS M ) and Low Priority (CoS B ). The CoS of each session to be sent by the network depends on the type of protocol or traffic, for example, if a video session will require a better deal on the network, so their priority is high (CoS A ). In case, for example, a data session will be low priority (CoS B ). • Λ is the set of wavelengths available to allocate. Where Λ = λ α , λ β , λ γ . λ α is the subset of wavelengths with low dispersion, λ β the subset of wavelengths with a mean dispersion, λ γ the subset of wavelengths with high dispersion. Fig. 9. Standard section The model is based on the Residual Dispersion (RD), which is defined as the total dispersion in optical fiber transmission in a given fiber compensation. The model takes into account a standard section (Figure 9) and contains the following elements: • Single Mode Fiber (SMF): optical fiber designed to carry a single ray of light. The fiber may contain different wavelengths. It is used in DWDM. • Dispersion Compensating Fiber (DCF): Fibers responsible for controlling/improving the chromatic dispersion. It works by preventing excessive temporary widening of the light pulses and signal distortion. The DCF compensates the distortion accumulated in the SMF. • Length of SMF (L SMF ) • DCF length (L DCF ) • EDFA Amplifiers The model is intended to find the percentage of wavelengths with low (λ α ), medium (λ β ) and high dispersion (λ γ ), comparing the value of RD with a threshold. The model is defined as follows: Inputs: • B: Compensation Factor (Dispersion Slope) [ps/nm 2 km]. • Λ: set of wavelengths available to allocate. Λ = λ 1 , λ 2 , , λ w . Where w is the number of wavelengths. 321 Physical Layer Impairments in the Optimization of the Next-Generation of All-Optical Networks 10 Will-be-set-by-IN-TECH • λ re f : reference wavelength [nm]. It depends on the bandwidth of the channels. The parameters are available in the Rec G.694.1. • Threshold: threshold of acceptance [ps/nm]. Threshold = 1000 ps/nm for speeds of 10 Gbps. • D sm f : Coefficient of dispersion in the SMF for the reference wavelength [ps/nm.Km]. • D dc f : Coefficient of dispersion in the DCF for the reference wavelength [ps/nm.Km]. • L SMF : SMF length [km]. • L DCF : DCF length [km]. Outputs: Equations 1,2,3 help to obtain the parameters of RD, as shown in Equation 4. Δλ w = λ w −λ re f ; ∀w (1) ΔD w = Δλ w × B ; ∀w (2) D w = D λ re f + ΔD w ; ∀w (3) RD w = D w (SMF) × L SMF + D w (DC F) × L DCF (4) The RD parameter will be used for the allocation of wavelengths. The proposal seeks to allocate the wavelengths less DR sessions with higher priority (CoS A ). We used the cost function proposed in Ali Ezzahdi et al. (2006) (Threshold = 1000, other parameters were taken from Zulkifli et al. (2006)) to determine the value of RD (Equation 5). d ij × RD w ≤ threshold (5) Given the analysis performed, we conclude that the first 15% of the wavelengths have less residual dispersion, the dispersion medium below 60%, while the remaining 25% has high dispersion. These parameters will then be used for the assignment. 2.1.1 Proposed allocation model The WDM network is modeled by a connected directed graph G(V, E) where V is the set of nodes in the network with N = |V| nodes. E is the set of network links. Each physical link between nodes m and n is associated with a L mn weight, which can represent the cost of fiber length, the number of transceivers, the number of detection systems or other. The total cost of routing sessions unicast/multicast in the physical topology is given by equation 6: TotalCost = ∑ ik ∑ wW ∑ (m,n)N L mn · f i ·χ iw mn (6) Where: • N: Number of nodes in the network. • W: Maximum number of wavelengths per fiber. • bw i : Bandwidth required per session unicast/multicast i. • C w : Capacity of each channel or wavelength. For example, C w = OC-192 or OC-48. 322 Optical Fiber Communications and Devices Physical Layer Impairments in the Optimization of the Next-Generation of All-Optical Networks 11 • f i : Fraction of the capacity of a wavelength used for the session i. f i = bw i /C w . • k: a group of unicast or multicast sessions. • χ iw mn : Boolean variable, which equals one if the link between nodes m and n is occupied by the session i on wavelength w. Otherwise χ iw mn = 0. K sessions are considered unicast/multicast denoted by R i (S i , D i , Δ i )|i = 1, 2, , k . Each session R i is composed of a source node S i , node or set of destination nodes and a parameter D i class of service associated Δ i = CoS A , CoS M , CoS B . Δ i be determined by a model presented in the next subsection. Let T i (S i , D i , Δ i , λ i ) tree routing for the session R i in λ i wavelength. When R i is multicast, the message source S i to D i a tree along the t i is divided (split) on different nodes to route through the various branches of the tree to wound all nodes D i . The architecture of S/G Light-tree allows this operation. Regarding the degree of the node is supposed to be unlimited (bank splitter architecture S/G unlimited). In addition, the wavelength conversion are not considered. The wavelength conversion in all-optical half are expensive and are still under development. The objective of grooming, routing and allocation algorithm is to minimize the cost of the tree taking into account the dispersions present in the wavelengths. That is, the network has a set Λ = λ 1 , λ 2 = λ α , λ β , λ γ of wavelengths, which: λ α is the set of wavelengths of low dispersion, λ β is the set of half wavelength dispersion and λ γ all wavelengths of high dispersion. As obtained in the previous section: λ α is the first 15%, λ β 15% to 75% and λ γ the last 25% of wavelengths. The wavelength is assigned to a particular R i depend on the type of service required for that session Δ i . The main objective is given by the equation 7. Minimi ze ∑ ik ∑ wW ∑ (m,n)N L mn · f i ·χ iw mn (7) The problem of routing unicast/multicast is basically a minimum Steiner Tree problem, which is NP-hard. We propose a heuristic to find the tree predictive routing taking into account QoS (through CoS) and dispersions in all wavelengths. Another feature of the heuristic is trying to keep more spare capacity in the low wavelength dispersion for the sessions r i with Δ i = CoS A are most likely to access this resource. 2.1.2 Prediction using Markov chains Markov chains are a tool to analyze the behavior of some stochastic processes, which evolve in a non-deterministic over time to around a set of states. Using Markov chains to predict in different systems has been tested and validated for their efficiency in different systems of telecommunications. We use Markov chains to predict the possible CoS that come with the next session (in t + D t ). The states are defined as class of service (CoS) of a given session. The model applies for n types of CoS as shown in Figure 10. For the case study (3 CoS), we obtained the transition probabilities (P xy , where x and y are states that define the CoS) taking into account the available data traces of ACM SIGCOMM (Acm, 2000). From this data was obtained the following transition matrix: P xy = ⎡ ⎣ 0.1009 0.3082 0.5910 0.1007 0.3089 0.5905 0.1009 0.3083 0.5908 ⎤ ⎦ (8) 323 Physical Layer Impairments in the Optimization of the Next-Generation of All-Optical Networks [...]... distances without signal regeneration Large bandwidth, multiplexing capability Small size and light weight Inexpensive Optical Fiber Communications and Devices Drawbacks Unsuitable for electrical power transmission Fragile when handling Not easy to reconnect when broken Table 1 Advantages and drawbacks of optical fiber for data communication From the perspective of high speed digital data transmission... optical equipment in C-band (1550 nm) is relatively expensive, and optical transceivers typically used in digital data transmission electronic systems offer much lower data rates, up to 10 GHz, and a reach of a few hundreds of meters 2.2 Optical transceivers Optical transceivers are the interfaces between optic and electronic worlds They perform the optical data transmission and reception, so they integrate... to electronic domain, fiber optic as transmission medium, high-speed optical transceivers, electronic serializers/deserializers and digital signal processors, typically Field Programmable Gate Arrays (FPGAs) The main characteristics of each component will be identified, and their impact on the total system will be discussed 2.1 Optical fiber link The main advantages of optical fiber data links are those... High-Speed Optical Links J Torres, R García, J Soret, J Martos, G Martínez, C Reig and X Román Department of Electronic Engineering, University of Valencia, Valencia Spain 1 Introduction Optical fiber links offer very important benefits as EMI immunity, low losses, high bandwidth, etc, so an increasing number of communication applications are being developed and deployed At both sides of these optical. .. section, the optical fiber links components are described, emphasizing the main advantages of optical links for digital data transmission and discussing how high speed optical links are handled in the electronic domain In the second section, the fundamentals of Printed Circuit Board (PCB) design will be reviewed, including trace design and routing, multilayer PCBs, electromagnetic interferences and clock... high energy nuclear experiments Optical fibers have inherent inmunity to most forms of EMI, since no metallic wires are present So, the optical fiber links ability of operating under severe EMI conditions is extremly important for a great number of applications, especially in defense, health and telecommunication sectors The second most important advantage of optical fiber links for high speed data... dispersion Dc (dispersion slope dDc /dλ) and the fiber length and can be determined as shown in equation 12 η= α2 4e−αL sin2 (Δβ · L/2) 1+ α2 + Δβ2 (1 − e−αL /2) (12) 330 18 Optical Fiber Communications and Devices Will-be-set-by-IN-TECH Where: 2πλ2 0 c 2 λ0 dDc 2c dλ Δβ = × (wi − wk )(w j − wk ) Dc + ( w i − w0 ) + ( w j − w0 ) (13) c is the speed of light in vacuum and λ0 is the wavelength on zero dispersion... wavelengths are exhausted If it is not possible to 326 14 Optical Fiber Communications and Devices Will-be-set-by-IN-TECH assign any wavelength, we proceed to eliminate this session is marked as blocked traffic The advantage of the algorithm is to use the CoS cycles are reduced search when looking for that wavelength can be assigned 2.2 Analysis and results of the proposed model The simulations are performed... frequencies 328 16 Optical Fiber Communications and Devices Will-be-set-by-IN-TECH (c) QoS: Low priority 0.55 0.5 0.45 Blocking Probability 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05 TG−QoS PredictionTG−QoS Standard assignment 0 10 20 30 40 50 Load (Erlangs) 60 70 80 90 100 Fig 15 Blocking Probability for CoSB , QoS: Low priority Comparison % Available Capacity 60 TG−QOS PredictionTG−QoS Standard assignment... management The pre and post-layout studies required for a proper design will be described in the third section, illustrating the explanation with some considerations about real designs for electronic experiments using high speed optical links 2 High speed optical link components In this section the main components of high-speed optical links are identified and described These components are, from optical to . all 316 Optical Fiber Communications and Devices Physical Layer Impairments in the Optimization of the Next-Generation of All -Optical Networks 5 Fig. 1. NSFNet network. Sessions S 1 and S 2 in. of traffic, close to CoS A and CoS M supplied. 326 Optical Fiber Communications and Devices Physical Layer Impairments in the Optimization of the Next-Generation of All -Optical Networks 15 0 10. dispersion. 2. Non-linear optical effects: Four-wave mixing (FWM), Selfphase modulation (SPM), Cross-phase modulation (XPM), Stimulated Raman scattering (SRS). 320 Optical Fiber Communications and Devices Physical